MétaCan
Menu
Back to cohort
Record W2762321513 · doi:10.1145/3132272.3132291

Ambient Notifications with Shape Changing Circuits in Peripheral Locations

2017· article· en· W2762321513 on OpenAlex
Lee Jones, John McClelland, Phonesavanh Thongsouksanoumane, Audrey Girouard

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
TopicPersonal Information Management and User Behavior
Canadian institutionsCarleton University
Fundersnot available
KeywordsComputer scienceTask (project management)DistractionSet (abstract data type)EmbeddingPeripheralHuman–computer interactionElectronic circuitArtificial intelligenceEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

Calm technologies help us avoid distraction by embedding notifications in our surroundings with peripheral updates. However, users also lose out on the passive awareness that comes from more overt notifications. In our paper, we present an initial study setup on shape changing circuits as notifications. We compare near and far peripheral locations to determine the optimal location for these notifications by assigning a primary task of arithmetic questions, and a secondary task of responding to bend notifications. Our demonstration will show the set-up of our study to encourage discussion on possible applications of shape changing notifications in peripheral locations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.308
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.308
GPT teacher head0.433
Teacher spread0.125 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it